quote: Spot Bitcoin ETFs posted their heaviest weekly outflows since late June, with the 13 US-listed funds recording a net $389.7 million in redemptions during the week of August 10.
This reversed the prior week’s $853.5 million inflows—the strongest since April and spurred by a cold-wallet hack that temporarily boosted demand for regulated products.
Year-to-date flows stand near –$5.5 billion, leaving aggregate assets under management in the $77–80 billion range. BlackRock’s IBIT and Fidelity’s FBTC drove most of the withdrawals.
Bitcoin traded in a tight $63,000–$64,500 band, moving less than 2 percent on the week and remaining roughly 50 percent below its October 2025 peak near $126,000. Thirty-day implied volatility has fallen to around 37, signaling muted speculative interest.
Macro conditions offered little support. The Federal Reserve continues to hold the funds rate at 3.50–3.75 percent. July CPI printed 3.4 percent year-over-year with softer core readings, retail sales fell 0.6 percent, and employment cooled, prompting markets to price only about a 30 percent chance of a September hike.
Goldman Sachs has called such a move “very unlikely,” yet the 10-year yield sits near 4.68 percent and the 30-year has reached 5.3 percent—its highest since 2007—raising the opportunity cost of non-yielding assets.
Geopolitical tension has added further pressure. Escalating US-Iran friction, stalled peace efforts, and reduced shipping through the Strait of Hormuz have lifted Brent crude above $90 and WTI near $84–85, feeding inflation risks and keeping policy uncertainty elevated.
US equities, by contrast, have remained resilient. The S&P 500 closed near 7,745 (up about 13 percent year-to-date) and the Nasdaq around 26,645 (up roughly 14.6 percent), driven largely by AI and semiconductor names. Correlation with Bitcoin has stayed moderate at 0.3–0.5, yet prices have diverged: stocks advanced while Bitcoin stagnated.
ETF outflows therefore reflect more than short-term profit-taking. Higher real yields, energy-driven inflation risks, and selective equity strength leave Bitcoin without a clear institutional catalyst, keeping the token range-bound and flows volatile until rates ease or Middle East supply risks subside. | Spot Bitcoin ETFs recorded their largest outflows last week since the end of June, reversing a strong start to August https://www.bloomberg.com/news/articles/2026-08-17/bitcoin-etfs-see-largest-outflow-in-six-weeks-as-token-stagnates?taid=6a82a238659d87000122b04e&utm_campaign=trueanthem&utm_content=business&utm_medium=social&utm_source=twitter
85·ALong
n
news2h agonews
Spot Bitcoin ETFs posted their heaviest weekly outflows since late June, with the 13 US-listed funds recording a net $389.7 million in redemptions during the week of August 10.
This reversed the prior week’s $853.5 million inflows—the strongest since April and spurred by a cold-wallet hack that temporarily boosted demand for regulated products.
Year-to-date flows stand near –$5.5 billion, leaving aggregate assets under management in the $77–80 billion range. BlackRock’s IBIT and Fidelity’s FBTC drove most of the withdrawals.
Bitcoin traded in a tight $63,000–$64,500 band, moving less than 2 percent on the week and remaining roughly 50 percent below its October 2025 peak near $126,000. Thirty-day implied volatility has fallen to around 37, signaling muted speculative interest.
Macro conditions offered little support. The Federal Reserve continues to hold the funds rate at 3.50–3.75 percent. July CPI printed 3.4 percent year-over-year with softer core readings, retail sales fell 0.6 percent, and employment cooled, prompting markets to price only about a 30 percent chance of a September hike.
Goldman Sachs has called such a move “very unlikely,” yet the 10-year yield sits near 4.68 percent and the 30-year has reached 5.3 percent—its highest since 2007—raising the opportunity cost of non-yielding assets.
Geopolitical tension has added further pressure. Escalating US-Iran friction, stalled peace efforts, and reduced shipping through the Strait of Hormuz have lifted Brent crude above $90 and WTI near $84–85, feeding inflation risks and keeping policy uncertainty elevated.
US equities, by contrast, have remained resilient. The S&P 500 closed near 7,745 (up about 13 percent year-to-date) and the Nasdaq around 26,645 (up roughly 14.6 percent), driven largely by AI and semiconductor names. Correlation with Bitcoin has stayed moderate at 0.3–0.5, yet prices have diverged: stocks advanced while Bitcoin stagnated.
ETF outflows therefore reflect more than short-term profit-taking. Higher real yields, energy-driven inflation risks, and selective equity strength leave Bitcoin without a clear institutional catalyst, keeping the token range-bound and flows volatile until rates ease or Middle East supply risks subside.
85·ALong
n
news3h agonews
SanDisk Is Up 3,585%: Traders think it has more to run
The best-performing large cap in America over the past eighteen months is not an AI lab, a GPU designer, or a datacenter REIT. It is SanDisk, the company that made the memory card in your old camera. It listed at $48.60 on February 24, 2025, spun off from Western Digital to broad indifference. On Friday it closed at $1,790.82.
That is 3,585% in eighteen months, 49% of it in the last five sessions, and at roughly $278 billion of market cap it is now a top-30 US company.
Note: this is a stub of the full article on Hypercall Insights. Because of X platform limitations, the dropdowns, interactive components, and live data tools are not embedded here- read the full piece (with everything that did not fit) at https://insights.hypercall.xyz/sndk-supercycle-pricing-2026-08-17
Why is it performing so well? And what can the options market tell us about SanDisk's prospects? Let's start with the thesis.
AI inference is a storage problem
Everyone knows AI runs on GPUs and HBM. That story is three years old and fully priced. The newer, less-priced story is what happens one tier down.
A one-minute primer, for anyone who needs it. DRAM is working memory: each bit is a tiny capacitor that leaks, so it needs constant refresh and loses everything when power cuts, reads in nanoseconds, and costs real money per gigabyte. HBM is not a different silicon technology, it is DRAM packaged differently: dies thinned, stacked 8 to 12 high, mounted millimeters from the GPU with thousands of parallel connections. Same bits, vastly wider pipe, several times the cost. NAND flash is storage: bits are trapped charge that stays put with the power off, cells stack in 3D by the hundreds of layers, so it costs roughly a hundredth of HBM per byte. The price is speed, microseconds instead of nanoseconds, and cells wear out with heavy writing. Every SSD, memory card, and phone is NAND. This is what SanDisk makes. (A good visual explainer of how flash works: youtube.com/watch?v=dZcszUj5szA)
Here is the hierarchy every AI system lives inside. Fast memory is tiny and obscenely expensive. Big storage is cheap and far too slow. Every byte an AI system touches has to find a home somewhere on this ladder:
HBM gets the headlines because it is bolted to the GPU. But HBM is sized for compute, not for state, and modern AI systems generate state in absurd quantities. Count what actually has to live somewhere:
Two of these deserve a closer look, because they are the ones growing fastest.
Weights: the four-orders-of-magnitude decade
Model parameters map almost one-to-one to bytes. When models were 1.5 billion parameters, weights were a rounding error. They are not a rounding error anymore:
The one force pushing the other way arrived in 2024: fp8 and int4 quantization plus sparse mixture-of-experts cut the bytes actually served per parameter by 2 to 4x. The totals exploded anyway. A frontier-class model is still measured in terabytes, and no serving fleet holds one copy. It holds a copy per node, per region, per fine-tune, per experiment. The weights themselves have become a distribution problem that only flash is fast enough and cheap enough to solve.
KV cache: the state that ate the datacenter
The really fun one is the KV cache, the keys and values every transformer layer stores for every token of context, the working memory of a conversation. Every token of context a transformer holds costs memory for the rest of the conversation, roughly half a megabyte per token for a 405B-class dense model. That sounds harmless until you multiply it by agents running million-token contexts and thousands of concurrent sessions. (The article has an interactive calculator here; the snapshot below shows one setting.)
Play with that for thirty seconds and you understand the entire trade. A handful of long-context sessions overwhelms the HBM on a node that costs as much as a house. The industry's answer is not "buy more HBM," because there is no more HBM. The answer is to tier the state: park cold conversations on flash, reload them when the user comes back. SanDisk management now sizes this single workload, KV cache offload, at 75 to 100 exabytes of potential 2027 demand. For scale, that is roughly a third of the entire industry's annual output, from a workload that barely existed two years ago.
Add the embeddings behind every RAG system, the checkpoints behind every training run, and the hundred-petabyte corpora that dataloaders hammer at random, and the conclusion writes itself: the marginal byte of AI infrastructure is increasingly a flash byte. Storage stopped being the boring aisle of the datacenter sometime in 2025. The market took a while to notice.
The shortage
Demand was only half of it. The 2022-23 memory bust was bad enough that every NAND maker cut capex and idled lines, so when AI demand arrived there was nothing spare to sell:
Flash fabs are not light switches. Contract NAND pricing is now forecast up 75 to 100%, and since a wafer costs the same to make at any selling price, most of that increase falls straight to margin. SanDisk says about two thirds of its June-quarter sequential growth came from price, not volume.
Implied vol across the storage complex shows how precisely the market has sorted this out:
Micron makes DRAM and HBM alongside NAND. Western Digital kept the hard drives. Seagate is drives with a NAND garnish. SanDisk is the only large-cap pure play on flash pricing, and it carries a 13 to 20 vol point premium over all of them, at every tenor, out to 2028. The purer the exposure, the wider the distribution.
Purity is priced. SNDK at 91% implied vol against Micron's 71% is not the market calling SanDisk a worse company. It is the market calling it the least-hedged bet on the same question. If NAND pricing holds, SNDK earns the most per dollar of market cap. If it cracks, there is no DRAM division to hide behind.
Datacenter took over in four quarters
That premium is earned. Revenue by end market, every quarter since the spin-off:
Datacenter went from $213 million to $2,977 million in four quarters and is now a third of revenue, growing 103% sequentially. Consumer, the SD cards the company was named after, shrank 5%. Even the boring Edge segment, flash sold into PCs and phones, quadrupled on pricing alone.
Margins are where it stops looking like a memory company at all:
84.6%. Gross margin, June quarter. A company selling a commodity into a spot market cannot print that. A company selling allocation of a scarce resource under contract can. For calibration: TSMC runs high-50s, Nvidia mid-70s, and SanDisk itself printed 26.2% a year ago.
The contracts
Those contracts got a dollar figure on August 13, at SanDisk's Investor Day: $93.9 billion of contracted business under its "New Business Model" agreements. Multi-year hyperscaler deals, quantities detailed by month, fixed price floors, financial guarantees. Ten signed, five since April. The stock rose 49% that week.
Management's fiscal 2028-2030 targets off this base: mid-to-high-teens revenue growth, gross margins around 80%, free cash flow margins near 50%, a buyback authorization now at $15.5 billion. Toll-road economics, if you believe them.
The bull case for the contracts is that they break the destocking spiral that made every previous memory downturn worse. Customers with take-or-pay floors do not run down inventory on a whim, and a hyperscaler signing four years of volume is showing you its own internal demand forecast.
The bear case is polysilicon. After 2011, ten-year take-or-pay contracts got renegotiated, litigated, or simply walked once spot fell far enough below contract. Long-term agreements dampen cycles; they do not repeal them. What $93.9 billion really buys is a change of question, from "will demand hold" to "will these prices hold when supply arrives." A better fight. Still a fight.
HBF: flash on the GPU package
There is one more leg, further out, and it needs a paragraph of packaging to make sense.
HBM is fast for a packaging reason, not a silicon one. Take ordinary DRAM dies, thin them, stack eight or twelve high, drill thousands of vertical connections through the stack, and mount the whole thing millimeters from the GPU on a shared slab of silicon. Width does the work: the stack talks to the GPU over thousands of wires at once, which is how you get terabytes per second out of memory that is not individually fast. The cost is capacity. DRAM cells are large, stacks have height and heat limits, and you end up with 36 to 48 GB per stack of the most expensive memory ever mass-produced.
High Bandwidth Flash is the same packaging trick with NAND dies in the stack instead of DRAM. NAND stores an order of magnitude more bits per die, so the published spec lands at 512 GB per stack at 1.6 TB/s: HBM-class bandwidth, more than ten times HBM capacity.
Flash has two real handicaps as memory. Reads take microseconds instead of nanoseconds, and cells wear out if you write them constantly. Both handicaps miss the inference workload almost entirely. Weights are written once and read billions of times. KV cache reloads are big sequential streams, the one access pattern where flash latency hides behind bandwidth. HBF would be useless as general-purpose memory, and it is not aimed at general-purpose memory. It is aimed at the workload from the first section of this piece.
If it ships, eight stacks put about 4 TB next to one accelerator, room for an entire frontier model's weights on the package, where today's HBM holds a fraction of them. SanDisk co-authored the spec with SK hynix and published it through the Open Compute Project in early August. First samples are due in the second half of 2026, first inference devices in early 2027.
None of it is in current earnings, and none of it should be modeled as revenue. It is a call option stapled to the stock: right partner, open standard, right workload. Paying something for it is reasonable.
Whose news moves whom
SanDisk, Micron, Western Digital, and Seagate now trade as one macro bet. SNDK and MU daily returns have correlated at 0.85 over the past 60 days. The options market prices them together too, but not identically, and the differences are where the information is.
The level difference is the purity premium from earlier: SNDK at 91%, the rest 13 to 20 points below, at every tenor. Same question, different leverage to the answer.
The more interesting difference is what each surface says about whose news matters. Micron reports on roughly September 22. None of the other three companies has any event that week. Their forward curves know anyway:
Micron's own report week prices 12 points over its neighbors, which is what an earnings week looks like. But Seagate, with nothing on its calendar, carries the same 12-point bump, and SanDisk carries five and a half. Only Western Digital, the one name with no NAND on the income statement, sleeps through it. In a shortage, the first supplier to disclose contract pricing moves everyone who sells flash.
Run the test backwards and it fails. SanDisk reports November 5, and its own forward for that window runs 96.7%, eleven points over base. Micron's forward through the same window: 71.2%, between a 70.0% stretch before and 69.0% after. SanDisk's biggest day of the year does not exist on Micron's surface. The market has decided information flows one way down this supply chain, from the diversified bellwether to the leveraged pure play, never back.
The leverage is quantifiable. Total variance across SNDK's expiries fits base-plus-events with about one vol point of error: 85.8% base, plus a 17.7% move for each of the next seven earnings reports. The same fit on Micron gives 70.6% and 4.2%. A Micron print is a data point. A SanDisk print is a referendum, priced at roughly double anything SanDisk has actually delivered:
We do not think that repricing is crazy. Under the NBM model, earnings day became the day the contracted book gets marked in public: new signings, new floors, new customers. November 5 is the first print against both the $10.3 to $10.8 billion guide and the Investor Day targets.
The far end of the curve makes the same point on a longer clock:
The top of the entire curve, 99.4%, sits in the first half of 2028, and stays at 91.3% even after stripping out both earnings reports inside that window. That is not an earnings hump. It lines up with the industry's own supply calendar:
Until late 2027 the shortage is unfalsifiable: no quarter can prove the bears right while the fabs that could oversupply the market do not exist. The first real test of the $93.9 billion book against new capacity comes in 2028, and the surface has parked its maximum uncertainty exactly there.
The market prices the debate, not the answer. The last question in every SanDisk bull-bear argument is whether AI created a structural NAND supercycle or a spectacular but temporary squeeze. The options market's answer: still an open question in 2028, litigated in 17.7% increments every quarter until then, with the widest distribution of outcomes parked exactly where new supply can first arrive.
In dollars, here is the whole piece on one time axis: the realized path in, the implied distribution out:
A range of $509 to $6,361 by mid-2028 is the market holding both endings live: the commodity cycle in a party hat, and the structurally-80%-margin infrastructure company. The 25-delta risk reversal is inverted, calls over puts by 3 to 4 points at every expiry, so of the two tails, the market pays up for the melt-up. Meanwhile the equity trades near 10 times annualized guided earnings, a multiple that says "temporary." The stock and its own options are having an argument. We would rather own the argument than either side of it.
The bottom line
AI made storage a first-order input. That demand hit the one commodity whose supply had spent three years shrinking, at the purest-play supplier, which converted the squeeze into four years of contracts and margins no memory company has printed before. Nobody finds out whether it lasts until supply returns in 2028. Until then the path itself is priced: seven referendums at 17.7% each, a checkpoint every time Micron speaks, and a final exam in the first half of 2028.
SNDK is live on Hypercall. Everything in this piece, the term structure, the event pricing, the 2028 forwards, is a market you can trade, on-chain: app.hypercall.xyz/asset/sndk. The full interactive version, with the KV-cache calculator and the complete methodology, is at insights.hypercall.xyz/sndk-supercycle-pricing-2026-08-17.
Data, methods, sources, and caveats
80·ALong
n
news7h agonews
Correlated Pairs: How AMMs Win the Biggest Markets
I’ve spent 9 years working on the frontier of DeFi. It’s a fascinating surface area with infinite depth and the capability to transform capital markets. I’ve always believed in the massive potential of the AMM, but for the past decade, one big question nagged at me. Can this new market structure really become the core engine for all financial markets? It’s taken years of evolution and growth, but there’s an increasingly clear path to AMM global dominance forming. The best way to explain it starts in 1976. Tokenization changes who makes markets The index fund turns 50 this month. When Jack Bogle launched it in 1976, he hoped to raise $150 million. He collected $11.3 million. Rivals called it "Bogle's folly" and printed posters calling index funds un-American. A fund that made no decisions, they argued, could never beat professionals paid to make them. Today the majority of American fund assets sit in passive vehicles.
I've been thinking about this lately, because tokenization’s folly moment is ending. The SEC has approved Nasdaq and NYSE to trade tokenized shares. DTCC, which settles nearly every security in America, ran a live trial of tokenized trading in July. Nearly all this activity is described the same way: tokenization as an infrastructure upgrade. Same markets, faster, cheaper, always on. This is all true, but I think the upgrade framing buries the bigger story. Tokenization makes markets programmable: changing what markets exist, who makes them, and what those markets trade against. In 2018 I built Uniswap, a protocol that automates market making. Anyone can deposit two assets into a shared pool and earn a fee on every trade, while prices adjust along a curve as people buy and sell. Uniswap has run autonomously since the day it launched, settled more than $4.6 trillion in volume, and helped push decentralized exchanges from under 1% of centralized spot volume to over 20%. As AMMs like Uniswap have grown, their liquidity has organized into a pattern most of finance hasn’t noticed yet: correlated pairs. The easiest wins To win at everything, you have to start by winning something. AMMs found product-market fit in the long tail, where most assets couldn't get a professional market maker's attention at all. On Uniswap, anyone could create a market in one transaction, with issuers and early supporters as the first LPs. Stable pairs came next: on a pair like USDC/USDT, a good passive strategy gets close enough to optimal that a lower cost of capital more than covers the gap. This is why professional trading firms don’t bother market making these stable swaps today: they’re being undercut by passive AMMs. Big margins, no competition Traditional financial markets fully belong to market-making firms. They bundle capital, trading strategy, execution technology, settlement, and distribution into one vertically integrated business. The architecture evolved for good reasons. Assets lived in separate systems, settlement was slow, and someone had to perform every function, so one firm performed them all. With enough scale, all those fixed costs pay for themselves. Citadel Securities handles roughly 25% of American equity volume and produced a record $12.2 billion in net trading revenue last year on roughly $21 billion of trading capital. Most people read those numbers as proof the system works. I read them as entrenchment. Breaking the bundle Blockchains create competition at each layer, breaking the bundle apart. Execution happens through code. Custody and settlement are shared services anyone can plug into. What once required proprietary infrastructure is now open-source software. With AMMs, capital is the scarce input and the edge belongs to whoever holds inventory most cheaply. A trading firm needs high returns to justify its overhead, so an LP willing to accept less undercuts it. Most market makers hedge away all price exposure, and hedging costs money, so an investor who already holds the assets takes that exposure for free. And asset issuers have a negative cost of capital, since asset issuers typically have to pay professional market makers to market make on their new assets. Put simply, DeFi and AMMs lower the barrier to making markets, opening the space up to many new participants. Their edge can come from many different sources such as a lower cost of capital, desiring the inventory exposure professional firms would typically hedge, or even being the issuer themselves. But everything rests on one question: can automated strategies perform well enough for this to hold? Liquidity follows correlation Recently, I was on a call with one of the largest institutions in finance. They asked me what base pairs were most common in DeFi. I explained that Ethereum-based assets tend to trade against ETH, Solana assets against SOL, and stablecoins pair against each other, with a small number of highly liquid pairs bridging between these clusters.
No one designed that. It emerged organically, in part because LPs do best when the assets they hold move together. Correlation means less inventory risk for liquidity providers, deepening liquidity. As assets tokenize, the biggest markets in the world will reorganize the same way. They can't today. Traditional markets settle overwhelmingly in dollars out of necessity. Assets live in siloed systems, and fiat rails like SWIFT and Fedwire are the glue that holds everything together. But blockchains are a far more expressive glue. Tokenize the assets, and they share a settlement layer, so any asset can trade directly against any other. NVDA/USD can become NVDA/SPY, with SPY/USD as the bridge back to dollars. Oil companies can trade against an oil ETF or tokenized oil. Private credit can trade against tokenized Treasury funds. Tokenization also enables markets that span different types of assets, which is extremely difficult, if not infeasible, with TradFi infrastructure. Delta neutrality is inefficiency Traditional market making firms generally try to be “delta neutral” which is fancy traderspeak for denominating in dollars and wanting to minimize any non-dollar risk. When making a volatile asset they will pay money to reduce their non-dollar risk (aka hedging), usually through options. This is one of the higher cost aspects of traditional market making. Pairing assets into lower volatility “correlated pairs” connected by a few higher volatility “bridge pairs” brings numerous efficiency unlocks, but the most important one is that market making is cheaper and more efficient if the people market making on the assets actually want to hold the underlying assets. And the more correlated a pair, the smaller any gap between today’s passive AMM strategies and the most sophisticated active strategies, making it easier to “undercut” them with this lower inventory cost. To make it concrete, if someone is long NVIDIA, you’re probably also long SPY, and the gap in efficiency between passive AMMs and active strategies is much lower for NVIDIA/SPY than for NVIDA/USD. Connected liquidity If stocks trade against SPY instead, every trade that starts or ends in dollars routes through the same pair: SPY/USD. These bridge pairs still require sophistication, but there are much fewer of them, and they carry so much flow that professional attention is worth it. DeFi already proved this. ETH/USDC is one of the deepest markets onchain because every cluster routes through it. Passive LPs supply the correlated pairs, while active LPs compete over the bridge pairs. Investors can still buy and sell everything in dollars, since routing across pools is automatic. And liquidity will concentrate where risk is lowest, not where legacy plumbing requires it to sit. That pushes the deepest markets into correlated pairs, the ground where AMMs are already strongest. Correlated RWA pairs already exist Correlated onchain liquidity began with crypto native assets. But the first correlated markets for tokenized equities exist today: ten tokenized stocks trading against SPY, in Uniswap pools on Robinhood Chain. In their first twelve days, these pools did $33 million in volume from more than 11,000 traders, much of that while US markets were closed. Some trades went straight from one stock to another, never touching dollars
It’s worth mentioning we’ve also started seeing memecoins paired against “correlated” stocks: Elon memes paired against Tesla stock, hotdog memes against Costco stock. Unclear how correlated these will actually be in terms of price, but I guess “vibes” is another type of correlation. AMMs will win Correlated pairs are just one part of the puzzle. The other part is AMM design and customization. Uniswap v4 hooks enable full market customizations that can significantly improve LP returns, such as the DualPool hook we recently released, which puts passive AMM funds to work earning lending yield, when they’re not being used for swapping. Despite ~$4.6T in volume on Uniswap, I believe AMMs are still in their infancy, and there are many other paths that will improve their competitiveness. There are many other promising approaches to improving LP returns, being built internally by Labs and externally by our partners and ecosystem. A lot more here coming soon! The case against index funds in 1976 was that a fund making no decisions could never beat professionals paid to make them. Fifty years later, the fund that makes no decisions beats about 90% of the professionals. More importantly, index funds democratized investing and improved the lives of everyday people. I believe passive liquidity will win with a similar playbook, and have an even greater impact, by dramatically lowering barriers to creating and participating in markets.
75·ALong
H
Hanami17h agonews
Wrap Technologies (NASDAQ: WRAP) Selected to Support Florida Teacher Safety Training Program. Austin, Texas, United States, 17th August 2026, FinanceWire … Read More
The post Wrap Technologies (NASDAQ: WRAP) Selected to Support Florida Teacher Safety Training Program appeared first on FinanceWire - Financial Press Release Distribution, Finance PR.
5·CNeutral
H
Hanami17h agonews
Wrap Technologies (NASDAQ: WRAP) Selected to Support Florida Teacher Safety Training Program
5·CNeutral
H
Hanami17h agonews
Quantum BioPharma (NASDAQ: QNTM) (CSE: QNTM) Reports Lower Q2 Expenses, Advances Lucid-MS Into Phase 2. Austin, Texas, United States, 17th August 2026, FinanceWire … Read More
The post Quantum BioPharma (NASDAQ: QNTM) (CSE: QNTM) Reports Lower Q2 Expenses, Advances Lucid-MS Into Phase 2 appeared first on FinanceWire - Financial Press Release Distribution, Finance PR.
Greenland Mines (NASDAQ: GRML) Completes Skaergaard Bathymetric Survey, Advances 2026 Drill Program. Austin, Texas, United States, 17th August 2026, FinanceWire … Read More
The post Greenland Mines (NASDAQ: GRML) Completes Skaergaard Bathymetric Survey, Advances 2026 Drill Program appeared first on FinanceWire - Financial Press Release Distribution, Finance PR.
White House hosting major crypto meeting this week…
Expected attendance from President Trump, SEC Chairman Atkins, CFTC Chairman Selig, & executives from across crypto industry including Coinbase, Polymarket, Ripple, Gemini, etc.
Also expected to include major tradfi players like Nasdaq, NYSE, CME, DTCC, etc.
IMO, administration not waiting around for Clarity Act.
Garnering support for that would be great, but think they’ve already made decision to power ahead regardless.
Predict this meeting will strongly reinforce that message.
75·ALong
n
news8/16news
This Week in Virtuals: Eastworlds Becomes Unitree's Official Data and Deployment Partner
Now the largest source of humanoid G1 data outside of China. VEX entered the Chronos era, and HALO crossed 10 billion tokens served in its first full week.
Here's what shipped:
VIRTUALS 🟩 Our robotics division @eastworlds_io became @UnitreeRobotics' official Data and Deployment Partner and the largest source of Unitree G1 data outside China, averaging 200 hours of humanoid teleoperation data per week.
🟩 Welcomed the Zerith H1s: a new fleet purpose-built for teleoperation data collection in hospitality, working toward humanoids that operate autonomously in these environments.
ECOSYSTEM 🟩 @StrikeRobot_ai was accepted into the @awscloud Global Startup Program, meeting its institutional-funding requirement with capital raised through ACF alone.
🟩 @xmaquina closed its first xDEUS Staking Program and opened Program II: 1,000,000 more $DEUS over 90 days.
🟩 @wardenprotocol crossed 10 billion tokens served, no account or API key needed, plus $50,000 in trader rewards on the HALO/VIRTUAL pool through Aug 24.
🟩 @ProjectVEXai entered the Chronos era with VEX 0.2: faster execution, longer missions, Windows support, and nearly 2,000 agents live across four chains.
🟩 @KarmaWallet chose @global_dollar USDG as its settlement currency: $4.9M processed since launch, volume up 234%, and 6,960 users on the app.
🟩 @grid_arena unveiled Grid v2, where the multipliers are real: a 5410x Bitcoin call turned $6.99 into $37,835 in 24 hours.
🟩 @ethy_agent partnered with @grid_arena to put short-term prediction markets on autopilot, and entered the @okx wallet trading arena.
🟩 @WizzHQ shipped Wizz Wallet, one wallet across seven networks with send, swap, and bridge built in, and joined OpenAI for Startups.
🟩 @myrad_hq is now backed by @GoogleStartups: 15,000+ monthly active users one month out of beta and $10,000+ paid to contributors.
🟩 @bleeep_xyz shipped two integrations: verifiable backtesting via @Lighter_xyz and cross-chain access to 60+ networks via @lifiprotocol.
🟩 @axol_io and @xochi_fi brought in @NethermindSec to audit Xochi's PXE Bridge, a key step toward private settlement for agent-driven trades.
🟩 @tradeongtr launched Limit and Market orders across desktop and mobile, added KORU perps for South Korea exposure, and now covers 700+ meme launches.
🟩 @monvera_best introduced Groves: buy a curated portfolio of tokenized stocks in one transaction, settled straight into your own wallet.
🟩 @AgentiqAI open-sourced Portfolio Pilot, its AI trading app built with @DefinitiveFi: clone it, study it, build on top of it.
75·ALong
m
meme8/16meme
This Week in Virtuals: Eastworlds Becomes Unitree's Official Data and Deployment Partner
Now the largest source of humanoid G1 data outside of China. VEX entered the Chronos era, and HALO crossed 10 billion tokens served in its first full week.
Here's what shipped:
VIRTUALS
🟩 Our robotics division @eastworlds_io became @UnitreeRobotics' official Data and Deployment Partner and the largest source of Unitree G1 data outside China, averaging 200 hours of humanoid teleoperation data per week.
🟩 Welcomed the Zerith H1s: a new fleet purpose-built for teleoperation data collection in hospitality, working toward humanoids that operate autonomously in these environments.
ECOSYSTEM
🟩 @StrikeRobot_ai was accepted into the @awscloud Global Startup Program, meeting its institutional-funding requirement with capital raised through ACF alone.
🟩 @xmaquina closed its first xDEUS Staking Program and opened Program II: 1,000,000 more $DEUS over 90 days.
🟩 @wardenprotocol crossed 10 billion tokens served, no account or API key needed, plus $50,000 in trader rewards on the HALO/VIRTUAL pool through Aug 24.
🟩 @ProjectVEXai entered the Chronos era with VEX 0.2: faster execution, longer missions, Windows support, and nearly 2,000 agents live across four chains.
🟩 @KarmaWallet chose @global_dollar USDG as its settlement currency: $4.9M processed since launch, volume up 234%, and 6,960 users on the app.
🟩 @grid_arena unveiled Grid v2, where the multipliers are real: a 5410x Bitcoin call turned $6.99 into $37,835 in 24 hours.
🟩 @ethy_agent partnered with @grid_arena to put short-term prediction markets on autopilot, and entered the @okx wallet trading arena.
🟩 @WizzHQ shipped Wizz Wallet, one wallet across seven networks with send, swap, and bridge built in, and joined OpenAI for Startups.
🟩 @myrad_hq is now backed by @GoogleStartups: 15,000+ monthly active users one month out of beta and $10,000+ paid to contributors.
🟩 @bleeep_xyz shipped two integrations: verifiable backtesting via @Lighter_xyz and cross-chain access to 60+ networks via @lifiprotocol.
🟩 @axol_io and @xochi_fi brought in @NethermindSec to audit Xochi's PXE Bridge, a key step toward private settlement for agent-driven trades.
🟩 @tradeongtr launched Limit and Market orders across desktop and mobile, added KORU perps for South Korea exposure, and now covers 700+ meme launches.
🟩 @monvera_best introduced Groves: buy a curated portfolio of tokenized stocks in one transaction, settled straight into your own wallet.
🟩 @AgentiqAI open-sourced Portfolio Pilot, its AI trading app built with @DefinitiveFi: clone it, study it, build on top of it.
75·ALong
n
news8/16news
This Week in Virtuals: Eastworlds Becomes Unitree's Official Data and Deployment Partner
Now the largest source of humanoid G1 data outside of China. VEX entered the Chronos era, and HALO crossed 10 billion tokens served in its first full week.
Here's what shipped:
VIRTUALS
🟩 Our robotics division @eastworlds_io became @UnitreeRobotics' official Data and Deployment Partner and the largest source of Unitree G1 data outside China, averaging 200 hours of humanoid teleoperation data per week.
🟩 Welcomed the Zerith H1s: a new fleet purpose-built for teleoperation data collection in hospitality, working toward humanoids that operate autonomously in these environments.
ECOSYSTEM
🟩 @StrikeRobot_ai was accepted into the @awscloud Global Startup Program, meeting its institutional-funding requirement with capital raised through ACF alone.
🟩 @xmaquina closed its first xDEUS Staking Program and opened Program II: 1,000,000 more $DEUS over 90 days.
🟩 @wardenprotocol crossed 10 billion tokens served, no account or API key needed, plus $50,000 in trader rewards on the HALO/VIRTUAL pool through Aug 24.
🟩 @ProjectVEXai entered the Chronos era with VEX 0.2: faster execution, longer missions, Windows support, and nearly 2,000 agents live across four chains.
🟩 @KarmaWallet chose @global_dollar USDG as its settlement currency: $4.9M processed since launch, volume up 234%, and 6,960 users on the app.
🟩 @grid_arena unveiled Grid v2, where the multipliers are real: a 5410x Bitcoin call turned $6.99 into $37,835 in 24 hours.
🟩 @ethy_agent partnered with @grid_arena to put short-term prediction markets on autopilot, and entered the @okx wallet trading arena.
🟩 @WizzHQ shipped Wizz Wallet, one wallet across seven networks with send, swap, and bridge built in, and joined OpenAI for Startups.
🟩 @myrad_hq is now backed by @GoogleStartups: 15,000+ monthly active users one month out of beta and $10,000+ paid to contributors.
🟩 @bleeep_xyz shipped two integrations: verifiable backtesting via @Lighter_xyz and cross-chain access to 60+ networks via @lifiprotocol.
🟩 @axol_io and @xochi_fi brought in @NethermindSec to audit Xochi's PXE Bridge, a key step toward private settlement for agent-driven trades.
🟩 @tradeongtr launched Limit and Market orders across desktop and mobile, added KORU perps for South Korea exposure, and now covers 700+ meme launches.
🟩 @monvera_best introduced Groves: buy a curated portfolio of tokenized stocks in one transaction, settled straight into your own wallet.
🟩 @AgentiqAI open-sourced Portfolio Pilot, its AI trading app built with @DefinitiveFi: clone it, study it, build on top of it.
75·ALong
n
news8/16news
Strategy ($MSTR) Challenges MSCI’s Latest Bid to Sideline It from Global Equity Indexes. Bitcoin treasury firm Strategy (NASDAQ:MSTR), which is led by tech billionaire Michael Saylor and formerly known as MicroStrategy, has publicly opposed a fresh proposal from index provider MSCI that could force its removal from major global equity benchmarks. Digital assets are assets. Index providers should measure... Read More
75·ALong
n
news8/15news
SpaceX Completes Acquisition of Cursor, Advancing AI Compute Strategy. SpaceX (NASDAQ:SPCX) has officially completed its acquisition of Cursor, the rapidly growing artificial intelligence coding platform developed by Anysphere. The deal, valued at $60 billion in an all-stock transaction, closed on August 14, 2026, marking a significant step in the rocket company’s broader push into... Read More
75·ALong
n
news8/14news
Gemini Space Station ($GEMI) Stock Drops following $108M Quarterly Loss Report. Shares of Gemini Space Station (NASDAQ: GEMI), the platform founded by Cameron and Tyler Winklevoss, slipped over 7% following the release of results for the quarter ended June 30, 2026. The digital assets focused company, which now also offers stocks trading, posted a net loss... Read More
75·AShort
m
meme8/13meme
WALL STREET TRADERS DROVE STOCKS HIGHER AND BOND YIELDS FELL AS MORE EVIDENCE OF MODERATING INFLATION REINFORCED BETS THE FED WILL REFRAIN FROM RAISING RATES NEXT MONTH, WITH BACK-TO-BACK GAINS DRIVING THE S&P 500 TO A RECORD AND THE NASDAQ 100 UP 1.1%, AS MONEY MARKETS PRICED IN LESS THAN A 40% CHANCE OF A SEPTEMBER HIKE AND OIL DROPPED TO AROUND $81.
85·ALong
n
news8/13news
The S&P 500 closed at a new record on Thursday, buoyed by cooler-than-expected inflation data and falling oil prices.
The broad market index added 0.65% and surpassed 7,800 for the first time ever, while the Nasdaq Composite gained 0.81%. The Dow Jones Industrial Average inched up 0.13%. https://www.cnbc.com/2026/08/12/stock-market-today-live-updates.html?__source=twitter|main
85·AShort
l
listing8/13listing
Binance: 币安期货将推出多个以美元Ⓢ为保证金的TradFi永续合约（2026年8月14日）
- - - - - - - - -Notice Details- - - - - - - - - - -
This is a general Binance Exchange Notice and a Notice for the purposes of the Clearing Rules. Products and services referred to here may not be available in your region.
Fellow Binancians,
To expand the list of trading choices offered on Binance Futures and enhance users’ trading experience, the following contract(s) will be admitted to trading on Binance RIE and admitted to Clearing and Settlement by Binance RCH at the time specified below:
2026-08-14 02:00 (UTC): ZHONGJIUSDT USDT-Priced Perpetual Contract 2026-08-14 02:05 (UTC): SAMSUNGEMUSDT USDT-Priced Perpetual Contract 2026-08-14 02:10 (UTC): HANMIUSDT USDT-Priced Perpetual Contract 2026-08-14 02:15 (UTC): LGELECTRONICSUSDT USDT-Priced Perpetual Contract 2026-08-14 02:20 (UTC): NAVERUSDT USDT-Priced Perpetual Contract 2026-08-14 02:25 (UTC): KODEX200USDT USDT-Priced Perpetual Contract
More details on the aforementioned perpetual contract(s) can be found in the table below:
Contract TypeUSDT-PricedUSDT-PricedUSDT-PricedUSDT-PricedUSDT-PricedUSDT-PricedUSDⓈ-M Perpetual ContractZHONGJIUSDTSAMSUNGEMUSDTHANMIUSDTLGELECTRONICSUSDTNAVERUSDTKODEX200USDTLaunch Time2026-08-14 02:00 (UTC)2026-08-14 02:05 (UTC)2026-08-14 02:10 (UTC)2026-08-14 02:15 (UTC)2026-08-14 02:20 (UTC)2026-08-14 02:25 (UTC)Underlying Equity/IndexZhongJi Innolight Co., Ltd. - H Shares (HKEX: 3308)Samsung Electro-Mechanics Co Ltd(KRX:009150)HANMI Semiconductor Co., Ltd.(KRX: 042700)LG Electronics Inc(KRX: 066570)NAVER Corp(KRX: 035420)Samsung KODEX 200 ETF(KRX: 069500)Settlement AssetUSDTUSDTUSDTUSDTUSDTUSDTTick Size0.010.010.010.010.010.01Min Trade Amount0.01 ZHONGJI0.01 SAMSUNGEM0.01 HANMI0.01 LGELECTRONICS0.01 NAVER0.01 KODEX200Min Notional Value5 USDT5 USDT5 USDT5 USDT5 USDT5 USDTCapped Funding Rate+2.00% / -2.00%+2.00% / -2.00%+2.00% / -2.00%+2.00% / -2.00%+2.00% / -2.00%+2.00% / -2.00%Funding Fee Settlement FrequencyEvery Eight HoursEvery Eight HoursEvery Eight HoursEvery Eight HoursEvery Eight HoursEvery Eight HoursInterest Rate of Funding Rate0%0%0%0%0%0%Maximum Leverage20x20x20x20x20x20xTrading Hours24/724/724/724/724/724/7Multi-Assets ModeSupportedSupportedSupportedSupportedSupportedSupported
Please Note:
This information is released as a Notice under Rules 75 and 89 of the Exchange Rules and a Notice under Rule 76.6 of the Clearing Rules.The aforementioned perpetual contract(s) are exempted from the 8.1 Adjustment of Funding Interval rules. The funding interval will not be adjusted from every eight hours to every one hour when the previous funding rate settlement of the aforementioned perpetual contract(s) reach the funding rate cap or floor.
Binance RIE may adjust the trading parameters of the aforementioned Contract[s] from time to time, in accordance with the Exchange Rules and the Exchange Procedures. The applicable trading parameters at any time are set out in the relevant Contract Specifications and in the Trading Parameters Table (USDS-M Futures). Binance RCH may adjust the maximum leverage and margin requirements in accordance with the Clearing Rules and the Clearing Procedures. The applicable maximum leverage and margin requirements are set out in the Leverage & Margin Table (USDⓈ-M Futures). Binance RCH may adjust the funding rate in accordance with the Clearing Rules and the Clearing Procedures. The applicable funding rate parameters are set out in the Funding Rate Table (USDⓈ-M Futures).There may be discrepancies between this original content in English and any translated versions. Please refer to the original English version for the most accurate information, in case any discrepancies arise.
More Information:
Perpetual Futures on Traditional AssetsTrading ParametersLeverage and Margin of USDⓈ-M Futures Contracts
Binance Futures Fee StructureHow to Select Trading PairsMark Price and Price IndexMulti-Assets ModeBinance Futures Contract Specifications
Thank you for your support!
Binance Team
2026-08-13